Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 59,931 to 59,940 of 228,014 articles

VIAFormer: Voxel-Image Alignment Transformer for High-Fidelity Voxel Refinement

arXiv Jan 20, 2026
We propose VIAFormer, a Voxel-Image Alignment Transformer model designed for Multi-view Conditioned Voxel Refinement--the task of repairing incomplete noisy voxels using calibrated multi-view images as guidance. Its effectiveness stems from a synergi... read more 
Computer Vision and Pattern Recognition

VIAFormer: Voxel-Image Alignment Transformer for High-Fidelity Voxel Refinement

arXiv Jan 20, 2026
We propose VIAFormer, a Voxel-Image Alignment Transformer model designed for Multi-view Conditioned Voxel Refinement--the task of repairing incomplete noisy voxels using calibrated multi-view images as guidance. Its effectiveness stems from a synergi... read more 
Computer Vision and Pattern Recognition

Transformer based Multi-task Fusion Network for Food Spoilage Detection and Shelf life Forecasting

arXiv Jan 20, 2026
Food wastage is one of the critical challenges in the agricultural supply chain, and accurate and effective spoilage detection can help to reduce it. Further, it is highly important to forecast the spoilage information. This aids the longevity of the... read more 
Computer Vision and Pattern Recognition

Finally Outshining the Random Baseline: A Simple and Effective Solution for Active Learning in 3D Biomedical Imaging

arXiv Jan 20, 2026
Active learning (AL) has the potential to drastically reduce annotation costs in 3D biomedical image segmentation, where expert labeling of volumetric data is both time-consuming and expensive. Yet, existing AL methods are unable to consistently outp... read more 
Computer Vision and Pattern Recognition

Dynamic Differential Linear Attention: Enhancing Linear Diffusion Transformer for High-Quality Image Generation

arXiv Jan 20, 2026
Diffusion transformers (DiTs) have emerged as a powerful architecture for high-fidelity image generation, yet the quadratic cost of self-attention poses a major scalability bottleneck. To address this, linear attention mechanisms have been adopted to... read more 
Computer Vision and Pattern Recognition

Who Should Have Surgery? A Comparative Study of GenAI vs Supervised ML for CRS Surgical Outcome Prediction

arXiv Jan 20, 2026
Artificial intelligence has reshaped medical imaging, yet the use of AI on clinical data for prospective decision support remains limited. We study pre-operative prediction of clinically meaningful improvement in chronic rhinosinusitis (CRS), definin... read more 
Machine Learning cs.AI cs.CL

EEG-Titans: Long-Horizon Seizure Forecasting via Dual-Branch Attention and Neural Memory

arXiv Jan 20, 2026
Accurate epileptic seizure prediction from electroencephalography (EEG) remains challenging because pre-ictal dynamics may span long time horizons while clinically relevant signatures can be subtle and transient. Many deep learning models face a pers... read more 
Machine Learning cs.HC

HiT: History-Injection Transformers for Onboard Continuous Flood Change Detection

arXiv Jan 20, 2026
Natural disaster monitoring through continuous satellite observation requires processing multi-temporal data under strict operational constraints. This paper addresses flood detection, a critical application for hazard management, by developing an on... read more 
Computer Vision and Pattern Recognition cs.LG

HiT: History-Injection Transformers for Onboard Continuous Flood Change Detection

arXiv Jan 20, 2026
Natural disaster monitoring through continuous satellite observation requires processing multi-temporal data under strict operational constraints. This paper addresses flood detection, a critical application for hazard management, by developing an on... read more 
Computer Vision and Pattern Recognition cs.LG

Principled Latent Diffusion for Graphs via Laplacian Autoencoders

arXiv Jan 20, 2026
Graph diffusion models achieve state-of-the-art performance in graph generation but suffer from quadratic complexity in the number of nodes -- and much of their capacity is wasted modeling the absence of edges in sparse graphs. Inspired by latent dif... read more 
Machine Learning
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